The Pragmatic AI Marketing Stack: Categories Over Tool Hype

When I ran more than 100 social media profiles with over 20 million fans at Mediengruppe RTL, a vendor showed up almost every week with a tool that was supposedly going to change everything. Most of those tools no longer exist. What stayed with me is a lesson that has helped in every project since: the tool is not the decision. The real question is which problem it solves in your actual daily work.

Today I build AI products myself, as an AI consultant at BE BRAVE AG and co-founder of ORION AI. More than 30 of them run in production: voice agents on the phone, live translation for streams, content automation. And I still tell every client the same thing: forget the tool lists. Think in categories. Tools come and go. The jobs in your marketing stay remarkably stable.

Six categories that cover any marketing operation

A pragmatic AI marketing stack has six categories: text (posts, newsletters, product copy), image (visuals, ad creatives, variants), video (editing, subtitles, formats for different channels), audio (voiceovers, podcast editing, voice assistance), automation (workflows that move content from A to B), and analytics (what works, what does not, and why). If you have one solid answer per category, you are better equipped than most large companies.

The advantage of this view: you can swap tools without your system falling apart. At Phantasialand, a theme park with around two million visitors a year, we ran completely different campaigns every season. What carried us was never a single tool but a clear process: who creates what, at which quality, for which channel. That process is your stack. AI just fills the gaps faster.

Selection criteria: how to filter out the hype

Before you subscribe to a tool, ask it the same questions you would ask a new hire during a trial month. Sounds obvious, rarely happens. Most subscriptions are born out of excitement after a LinkedIn video and die three months later, unused, on a credit card statement. From building our own products, six criteria have proven reliable at filtering out the hype:

• Does it solve a problem you have this week? Not one you might have next year.
• Does it fit your existing workflow, or would you have to rebuild your day around the tool?
• Can you leave within 30 days, including a clean export of your data?
• Where does your data live, and what does the vendor do with it? An unclear answer is a no.
• Does the price beat the hours it actually saves? Calculated honestly, not optimistically.
• Is anyone on the team still using it after two weeks without being reminded? If not, cancel.

Make or buy: when building your own makes sense

My ground rule: buying is the default, building is the exception. An off-the-shelf tool for image editing or subtitles will always be cheaper than a custom build. Building pays off in two cases: when the process directly sets your business apart, or when sensitive data must not leave the house. We built our live translation for streams in English, French and Italian because that solution simply did not exist to buy.

In between sits a middle path that often gets overlooked: connecting existing AI models to your workflows through their interfaces, without developing everything yourself. For small businesses, that is often the best deal. But do the honest math: a custom build costs not just the initial work but maintenance, updates and the stress when something breaks at night. As CEO of Heroes Germany, an agency in Cologne, I saw how much time can flow into tool upkeep instead of impact.

Privacy: principles instead of panic

At BE BRAVE we work on sovereign Swiss AI infrastructure every day, so this topic is close to me. But you do not need a legal department to start clean. Three principles are enough. First, sort your data: public marketing copy is uncritical, customer data never is. Second, no personal data in free tools whose business model is your input. Third, check where each vendor processes data and whether a data processing agreement exists.

That sounds like a brake, but it is a filter. Ask these three questions and you will weed out the dubious vendors along the way. And here is the good news: the market has responded. For almost every category there are now providers hosting in Switzerland or the EU. You do not have to choose between privacy and capability. You just have to look a little closer than your competitors do.

Budget realism: what small businesses actually need

Now for the question that comes up in every conversation: what does this cost? The honest answer: less than you think, but differently than you think. For a small team, license costs for a solid stack usually land in the range of a decent mobile phone plan per person per month. The real cost block is time: onboarding, training, and rebuilding habits. If you do not budget for that, you pay twice.

My advice: start with the category that hurts the most. For most small businesses, that is text or automation. Introduce one tool, give it four weeks of real use, measure the time saved, and then decide on the next category. A stack grows like a team: one good hire after another, not everyone at once.

Conclusion: your stack is a process, not a shopping list

Six categories, six selection criteria, three privacy principles and a budget that honestly counts the time: that is the whole trick. No secret knowledge, no hundred tools, no hype. I have worked this way since the first professional Facebook livestream of a Klitschko fight, and only the tools inside the process have changed. That is exactly the point: the process stays, the tools rotate.

Take one hour this week and write down your six categories. Note what handles each job today and where the biggest gap is. That single page is worth more than any tool list on the internet. And if you hit a question that does not answer itself: write to me. Which gap in your stack would you like to talk about?